Process management is an enormous field that is divided into various sections. It is all about dealing with the crucial aspects of creating, managing, and implementing multiple architectures by minimizing all the obstacles in the process.
Among the essential constituents of process management; comes process mining, which can be seen as a blend of various technologies that help complete a project successfully, saving time and energy.
The primary purpose of process mining is to inspect the way processes work, how they originate, the hurdles that appear, and the techniques to minimize the barriers and upsets for a process’ improvisation.
Keep reading this blog as we will shed light on process mining, how it works, its benefits, and will compare it with RPA:
What is Process Mining?
Process mining can be defined as a process to examine and to keep an eye on the processes’ progress. Earlier process mining was done by conducting various workshops and consulting individuals to draw a picture of the processes.
Since everything has modernized with time, so have the process mining techniques as they have evolved from the traditional practices to more advanced and automated ways. These days, process mining is conducted by analyzing the already available data and displaying a process based on the information.
Process mining can be implemented on any process if the required data is available or stored in a system. It has made the visualization of your processes more effortless than ever before. You can use process mining to conduct an in-depth analysis, compare different strategies, monitor tasks, set benchmarks, and work on the data for improving processes.
Process Mining Benefits
Process Mining brings a series of benefits with its implementation since it is a solid upgrade from the weary traditional methods for analyzing data and project management. Let’s take a look at the salient advantages of process mining in this section:
1) Process Improvements & Error Detection
All the activities that are conducted for the initiation, processing and finalization of processes are shown by the process flow. A process flow includes all the anomalies, divergences, and missed steps to help you conclude better results.
A user can track the processes and check if anything goes against your target model, check for improvements, and make the needed amendments right on time. Not only that, but a process flow also informs you about the better methods, and you may implement them for improved results.
2) Timely Improvements
Process mining makes it quick and a lot simpler to get the results, so it also has the nature to accept the real-time changes in the market.
It also makes the process of setting goals easier, which helps in developing an all-encompassing, assertive, and long-term optimization strategy that’s also flexible and welcomes new changes without any problems.
Since many processes are running in parallel, it is impossible to monitor each project following a traditional approach. Process mining provides more clarity in process management, as it shows the progress of all processes, whether running alone or in parallel to other processes.
Earlier, the visibility was quite tricky since there was a lot of paperwork involved, and with bigger projects, it was nearly impossible to track every process. Gone are the days when you had to guess if a process was failing or successfully running; with process mining, you get a clear picture of the progress of all processes.
4) Quick Results
Since process mining follows the latest approaches for optimization, it dramatically increases the pace of results. Rather than spending hours on paperwork and analysis, mining does your job in a matter of seconds.
5) Easy Monitoring
Process mining displays all your processes in great detail so that you can bring about changes at any phase to improve your processes. It allows you to either enhance the whole process or just work on the snippets of a process. All this helps you in developing a better strategy.
On top of that, process mining also allows you to check how your optimizations are affecting your processes and change the strategy at any point for better results.
Process Mining and Robotic Process Automation (RPA)
Process mining has been used effectively to analyze the current state of business process performance, identify areas of improvement, and assess the results of process improvements.
With process mining, you get a clear, data-driven picture of how well a process performs. The ability to see issues and solutions clearly will intrigue people working with process management. It will strengthen a company’s commitment to making decisions based on data.
Some businesses have already recognized process mining as a significant step in implementing RPA with better results. Many upcoming solutions will use a fusion of process mining, robotic process automation, and machine learning for best results.
How Do Process Mining and RPA Compare Against Each Other?
RPA handles all the tasks that are performed on a repeated basis, as it automates all those repetitive tasks to be done by robots in a faster and more efficient way. The RPA bots are handled via an application, and they imitate all the human actions that include regular tasks like adding, editing, removing, sorting the data, and much more.
Unlike RPA, which is a solution or a tool, process mining is more like a methodology, intending to turn data into useful information and take appropriate actions.
In order to digitize and automate business processes, businesses use process mining to analyze event log data for trends, correlations, and precise details about how a process develops. The new insights obtained from process mining can be used to eliminate corrupt data, efficiently allocate resources, and respond to any changes rapidly.
RPA automates business processes while process mining solutions help in the CRMs and ERP systems. Despite the fact that RPA and process mining are polar opposites, they work brilliantly together.
Benefits of Using Process Mining and RPA Together
Process mining and RPA are both powerful technologies but are lethal when they come together. They help your business in the following ways:
- Process mining and RPA complement each other as the former ads system event logs to gain insight into business processes, and the latter automates these processes.
- When used together, process mining improves the efficacy of bot operations and their deployment, which results in better results.
- Process mining increases the success rate of RPA projects.
Process Mining + RPA = Hyper-automation
Hyper-automation refers to the practice of automating everything that can be automated in a business. Think of it as a combination of RPA and process mining. Using AI, ML, and other technologies, organizations adopting hyper-automation aspire to streamline operations across their business so that they can function without human involvement.
Businesses implementing hyper-automation will find that process mining does much more than just identify areas for automation. The system also establishes links between different IT systems and reveals previously hidden workloads.
People mostly get confused figuring out the difference between automation and hyper-automation, so let’s clear how they differ once and for all.
Automation refers to the accomplishment of a routine task without the involvement of a human being. It’s more common on a micro level, with solutions tailored to specific problems. Hyper-automation pertains to using various automation tools for large-scale automation projects.
The tools used in process mining also produce data ready for machine consumption, allowing for the automated process’s robotic automation.
Hyper-automation can benefit an organization in myriad ways, including:
- Helping your workforce with teaching the right skillset.
- Improving your business via intelligence using Artificial Language and Machine Learning.
- Providing information on automating your ROI so that your business can continue to grow.
- Optimizing any business process using the latest technologies.
Process Mining and RPA Costs
Sure, process mining and RPA are not cheap. You might get scared a bit when looking at the costs of RPA and process mining. But here’s the thing. You need to calculate the value they are providing against their price.
Calculate how much labor costs you will be saving with their implementation. If we take into account the amounts that these tools help us save, then their amounts will look like nothing. Keep in mind that these tools aren’t built for struggling small businesses or individuals; but rather for enterprises.
Using RPA bots as a quick fix instead of tighter data integrations and improved ETL processes is quite common these days. RPA bots often hide technical debt by sitting on top of fragmented software landscapes.
Businesses can benefit from more intelligent automation. However, many organizations are better off unraveling their technical debt to enable simple data integrations and automation within their existing software rather than embarking on RPA expeditions.
In this technological era of development, anyone abstaining from the latest technological advancements will find themselves getting stuck in the web of problems.
All successful businesses are embracing process mining and robotic process automation to help them grow faster than ever. The combination of both RPA and process mining is lethal, so if you can afford it, then go for it.